FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313992146> ?p ?o ?g. }

• W4313992146 abstract "Mild traumatic brain injury (mTBI) is a major public health concern that can result in a broad spectrum of short-term and long-term symptoms. Recently, machine learning (ML) algorithms have been used in neuroscience research for diagnostics and prognostic assessment of brain disorders. The present study aimed to develop an automatic classifier to distinguish patients suffering from chronic mTBI from healthy controls (HCs) utilizing multilevel metrics of resting-state functional magnetic resonance imaging (rs-fMRI). Sixty mTBI patients and forty HCs were enrolled and allocated to training and testing datasets with a ratio of 80:20. Several rs-fMRI metrics including fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), degree centrality (DC), voxel-mirrored homotopic connectivity (VMHC), functional connectivity strength (FCS), and seed-based FC were generated from two main analytical categories: local measures and network measures. Statistical two-sample t-test was employed comparing between mTBI and HCs groups. Then, for each rs-fMRI metric the features were selected extracting the mean values from the clusters showing significant differences. Finally, the support vector machine (SVM) models based on separate and multilevel metrics were built and the performance of the classifiers were assessed using five-fold cross-validation and via the area under the receiver operating characteristic curve (AUC). Feature importance was estimated using Shapley additive explanation (SHAP) values. Among local measures, the range of AUC was 86.67-100% and the optimal SVM model was obtained based on combined multilevel rs-fMRI metrics and DC as a separate model with AUC of 100%. Among network measures, the range of AUC was 80.42-93.33% and the optimal SVM model was obtained based on the combined multilevel seed-based FC metrics. The SHAP analysis revealed the DC value in the left postcentral and seed-based FC value between the motor ventral network and right superior temporal as the most important local and network features with the greatest contribution to the classification models. Our findings demonstrated that different rs-fMRI metrics can provide complementary information for classifying patients suffering from chronic mTBI. Moreover, we showed that ML approach is a promising tool for detecting patients with mTBI and might serve as potential imaging biomarker to identify patients at individual level.[clinicaltrials.gov], identifier [NCT03241732]." @default.
• W4313992146 created "2023-01-10" @default.
• W4313992146 creator A5000438546 @default.
• W4313992146 creator A5033338919 @default.
• W4313992146 creator A5033687321 @default.
• W4313992146 creator A5042814171 @default.
• W4313992146 creator A5044189710 @default.
• W4313992146 creator A5046314699 @default.
• W4313992146 creator A5047458912 @default.
• W4313992146 creator A5049249441 @default.
• W4313992146 creator A5050756470 @default.
• W4313992146 date "2023-01-09" @default.
• W4313992146 modified "2023-10-14" @default.
• W4313992146 title "Identification of chronic mild traumatic brain injury using resting state functional MRI and machine learning techniques" @default.
• W4313992146 cites W1760829075 @default.
• W4313992146 cites W1948961139 @default.
• W4313992146 cites W1952204933 @default.
• W4313992146 cites W1964940342 @default.
• W4313992146 cites W1973776237 @default.
• W4313992146 cites W1996405315 @default.
• W4313992146 cites W2005238835 @default.
• W4313992146 cites W2007022499 @default.
• W4313992146 cites W2007213925 @default.
• W4313992146 cites W2009898156 @default.
• W4313992146 cites W2015895869 @default.
• W4313992146 cites W2020698869 @default.
• W4313992146 cites W2028602316 @default.
• W4313992146 cites W2028604962 @default.
• W4313992146 cites W2033376367 @default.
• W4313992146 cites W2039172538 @default.
• W4313992146 cites W2041406732 @default.
• W4313992146 cites W2043131801 @default.
• W4313992146 cites W2047492290 @default.
• W4313992146 cites W2053806135 @default.
• W4313992146 cites W2058046532 @default.
• W4313992146 cites W2064076048 @default.
• W4313992146 cites W2065895688 @default.
• W4313992146 cites W2068040649 @default.
• W4313992146 cites W2100240119 @default.
• W4313992146 cites W2100634972 @default.
• W4313992146 cites W2102669347 @default.
• W4313992146 cites W2105876678 @default.
• W4313992146 cites W2113330167 @default.
• W4313992146 cites W2157104415 @default.
• W4313992146 cites W2158485497 @default.
• W4313992146 cites W2170966360 @default.
• W4313992146 cites W2214908060 @default.
• W4313992146 cites W2223851414 @default.
• W4313992146 cites W2337323496 @default.
• W4313992146 cites W2417964944 @default.
• W4313992146 cites W2550693625 @default.
• W4313992146 cites W2559127480 @default.
• W4313992146 cites W2574580668 @default.
• W4313992146 cites W2581778384 @default.
• W4313992146 cites W2595085771 @default.
• W4313992146 cites W2598130805 @default.
• W4313992146 cites W2617855408 @default.
• W4313992146 cites W2620688866 @default.
• W4313992146 cites W2734388305 @default.
• W4313992146 cites W2747341096 @default.
• W4313992146 cites W2748415804 @default.
• W4313992146 cites W2768899399 @default.
• W4313992146 cites W2784551971 @default.
• W4313992146 cites W2799385785 @default.
• W4313992146 cites W2801765286 @default.
• W4313992146 cites W2884386142 @default.
• W4313992146 cites W2895699934 @default.
• W4313992146 cites W2899027966 @default.
• W4313992146 cites W2968068770 @default.
• W4313992146 cites W2968474362 @default.
• W4313992146 cites W2983706427 @default.
• W4313992146 cites W2991621876 @default.
• W4313992146 cites W2998311683 @default.
• W4313992146 cites W3011571399 @default.
• W4313992146 cites W3011742849 @default.
• W4313992146 cites W3013570887 @default.
• W4313992146 cites W3016748392 @default.
• W4313992146 cites W3037879998 @default.
• W4313992146 cites W3040949234 @default.
• W4313992146 cites W3045640841 @default.
• W4313992146 cites W3091839024 @default.
• W4313992146 cites W3093722097 @default.
• W4313992146 cites W3095444562 @default.
• W4313992146 cites W3102681366 @default.
• W4313992146 cites W3103729351 @default.
• W4313992146 cites W3106751704 @default.
• W4313992146 cites W3117989367 @default.
• W4313992146 cites W3132373197 @default.
• W4313992146 cites W3139182160 @default.
• W4313992146 cites W3161269039 @default.
• W4313992146 cites W3186153792 @default.
• W4313992146 cites W3189949146 @default.
• W4313992146 cites W4200278402 @default.
• W4313992146 cites W4200517765 @default.
• W4313992146 cites W4211148484 @default.
• W4313992146 cites W4220979755 @default.
• W4313992146 cites W4223949098 @default.
• W4313992146 cites W4225668959 @default.
• W4313992146 cites W4281785271 @default.
• W4313992146 cites W4283837412 @default.

• next